Investigating the association between wood and charcoal domestic cooking, respiratory symptoms and acute respiratory infections among children aged under 5 years in uganda: A cross-sectional analysis of the 2016 demographic and health survey

  • International Journal of Environmental Research and Public Health, Volume 17, No. 11, Year 2020

listen audio

Study Justification:
This study aimed to investigate the association between wood and charcoal domestic cooking, respiratory symptoms, and acute respiratory infections (ARI) among children under 5 years old in Uganda. The justification for this study is based on the significant health burden caused by household air pollution associated with biomass burning for cooking, particularly in low and middle-income countries. With 96% of households in Uganda using biomass as the primary domestic fuel, understanding the relationship between solid fuel type and respiratory symptoms is crucial for mitigating the harmful health impacts.
Highlights:
– The study analyzed data from the 2016 Demographic and Health Survey in Uganda, which included 15,405 pre-school aged children living in charcoal or wood-burning households.
– Multivariable logistic regression analysis was used to identify associations between respiratory symptoms (cough, shortness of breath, fever) and ARI with cooking fuel type (wood, charcoal).
– After adjusting for confounding factors, wood fuel use was associated with an increased risk of respiratory symptoms compared to charcoal fuel.
– Sub-analyses revealed that wood fuel usage was particularly associated with shortness of breath and ARI in urban areas, and ARI and fever in rural areas.
Recommendations:
Based on the findings of this study, the following recommendations can be made:
1. Promote the use of cleaner fuels (electricity, LPG, natural gas, biogas) as alternatives to solid biomass fuels (wood, charcoal) for cooking in households.
2. Implement awareness campaigns to educate communities about the health risks associated with wood fuel usage and the benefits of switching to cleaner fuels.
3. Provide financial incentives or subsidies to households to facilitate the adoption of cleaner cooking fuels.
4. Improve access to cleaner cooking technologies and infrastructure, particularly in rural areas.
5. Strengthen monitoring and enforcement of regulations related to household air pollution and cooking fuel quality.
Key Role Players:
To address the recommendations, the involvement of the following key role players is essential:
1. Government agencies responsible for energy, health, and environment policies and regulations.
2. Non-governmental organizations (NGOs) working in the fields of public health, environment, and sustainable development.
3. International organizations and donors supporting initiatives related to clean cooking and environmental health.
4. Community leaders and local authorities who can promote and facilitate the adoption of cleaner cooking fuels and technologies.
5. Researchers and academics who can provide expertise and guidance on the implementation and evaluation of interventions.
Cost Items for Planning Recommendations:
While the actual costs will vary depending on the specific interventions and context, the following cost items should be considered in planning the recommendations:
1. Research and data collection: Funding for surveys, data analysis, and research personnel.
2. Awareness campaigns: Costs associated with designing and disseminating educational materials, organizing community events, and conducting media campaigns.
3. Financial incentives or subsidies: Budget allocation for providing financial support to households for purchasing cleaner cooking fuels or technologies.
4. Infrastructure development: Investment in the establishment or improvement of infrastructure for the distribution and use of cleaner cooking fuels.
5. Monitoring and enforcement: Resources for monitoring compliance with regulations, conducting inspections, and enforcing penalties if necessary.
Please note that the above cost items are general categories and may need to be further detailed and refined based on the specific context and requirements of the interventions.

N/A

Background: Household air pollution associated with biomass (wood, dung, charcoal, and crop residue) burning for cooking is estimated to contribute to approximately 4 million deaths each year worldwide, with the greatest burden seen in low and middle-income countries. We investigated the relationship between solid fuel type and respiratory symptoms in Uganda, where 96% of households use biomass as the primary domestic fuel. Materials and Methods: Cross-sectional study of 15,405 pre-school aged children living in charcoal or wood-burning households in Uganda, using data from the 2016 Demographic and Health Survey. Multivariable logistic regression analysis was used to identify the associations between occurrence of a cough, shortness of breath, fever, acute respiratory infection (ARI) and severe ARI with cooking fuel type (wood, charcoal); with additional sub-analyses by contextual status (urban, rural). Results: After adjustment for household and individual level confounding factors, wood fuel use was associated with increased risk of shortness of breath (AOR: 1.33 [1.10–1.60]), fever (AOR: 1.26 [1.08–1.48]), cough (AOR: 1.15 [1.00–1.33]), ARI (AOR: 1.36 [1.11–1.66] and severe ARI (AOR: 1.41 [1.09–1.85]), compared to charcoal fuel. In urban areas, Shortness of breath (AOR: 1.84 [1.20–2.83]), ARI (AOR: 1.77 [1.10–2.79]) and in rural areas ARI (AOR: 1.23 [1.03–1.47]) and risk of fever (AOR: 1.23 [1.03–1.47]) were associated with wood fuel usage. Conclusions: Risk of respiratory symptoms was higher among children living in wood compared to charcoal fuel-burning households, with policy implications for mitigation of associated harmful health impacts.

Data for this cross-sectional study were obtained from the most recently available nationally representative Ugandan DHS [20], a population level survey implemented by the Uganda Bureau of Statistics (UBOS, supported by USAID, UNICEF, UNFPA) from 20 June to 28 December 2016 [21]. Two-stage stratified sampling was applied to identify eligible residential households across 697 enumeration areas (average 130 households) from 112 Districts and 15 regions in Uganda. From 20,791 eligible households, 18,506 resident ever-married women age 15–49 years were interviewed (98% response rate) [21]. Institutional living arrangements (e.g., boarding schools, police camps, army barracks, and hospitals) were excluded; as were households with no response at the time of fieldwork completion. Survey questionnaires were modified from those within the Phase VII DHS Program model, adapted to reflect the population and health issues relevant to Uganda. Information for this study was obtained from the (i) household questionnaire; comprising information on household structure, socio-demographic and housing characteristics, including domestic cooking fuel type, and; (ii) children’s questionnaire; including questions on maternal and child health outcomes and lifestyle characteristics. All survey fieldwork was undertaken within the participant’s home, by trained local fieldworkers supervised by senior staff, with data entry directly to tablet computers transferred to the UBOS central processing office by a secure internet system. Ethical approval for primary data collection was provided by the Uganda Ministry of Health. The investigators obtained the anonymised, aggregate data from the publicly available DHS online data archive [20] with authorization granted for data access for this current investigation on 16 June 2019. To assess respiratory symptoms, maternal respondents were asked if each of their children aged under 5 years had experienced the following symptoms within the two weeks prior to the survey: (i) a cough (ii) short rapid breaths or difficulty breathing (iii) a fever; each categorized and modelled as binary outcome measures (yes, no). A composite measure was created for both ARI and severe ARI, reflecting the presence of respiratory symptoms with or without fever, with each separately modelled as a binary health outcome measure (yes, no). ARI was classified as present of cough and short rapid breaths/difficulty [22], whereas severe ARI was composed of the presence of all three of these symptoms, (e.g., cough, short rapid breaths/difficulty breathing and fever) [23]. Among those households in which cooking activities were performed, self-reported cooking fuel types were identified from the household dataset and categorized as “cleaner fuels” (electricity, LPG, natural gas, biogas); “Solid biomass fuels and kerosene” (kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crop, animal dung) or other fuel types. Those mother-child pairs living in households reporting wood and charcoal fuel cooking were extracted for further analyses. Characteristics of household children comprised; age (0–11, 12–23, 24–35, 36–48, 48–59 months), sex (male, female), birthweight (kg, by maternal recall), weight for height (z score), mode of delivery (caesarean, vaginal), birth order (first, not first born), breastfeeding status (ever, never), vitamin A supplementation in the last 6 months (yes, no), iron supplementation (yes, no). Those children with diagnosed mild, moderate or severe anaemia (n = 2139) were excluded from further analyses, due to anaemia being a known factor for increased ARI risk [24], which could not be accounted for in the adjusted analyses due to the high quantity of missing data (2139/15405; 13.9%). Maternal characteristics included age (15–24, 25–35, 36–49 years) and highest attained educational level (none, primary, secondary/higher). Household characteristics were accounted for by the following variables: number of household members, indoor household smoking (yes, no), cooking location (inside, outdoors). Season at the time of DHS contact was determined from the month of interview and classified as dry (June to August) or wet (September to November) using information from the Central Intelligence Agency (CIA) fact book [25]. The five category DHS wealth index was used as a measure of household level socio-economic status (lowest, low, middle, high, highest). This composite measure reflects household ownership of selected assets (e.g., television, bicycle, car), dwelling characteristics (e.g., source of drinking water, sanitation facilities, types of cooking fuel, and floor material), with assessment of relative wealth category calculated by principle components analysis. Contextual characteristics comprised: place of residence (rural, urban), and country region (Kampala, South Buganda, North Buganda, Busoga, Bukedi, Bugisu, Teso, Karamoja, Lango, Acholi, West Nile, Bunyoro, Tooro, Ankole, Kigez). DHS classifies rural and urban area, as per the country of survey; in this case Uganda uses enumeration areas are defined as being rural or urban. Urban areas are defined as officially approved cities, municipalities, town councils and town boards [21], at the time which the survey was undertaken. All data processing, manipulation and analyses was performed using R studio [26]. Descriptive statistics were summarized by number of cases (n), percentages (%) (categorical variables) and median and interquartile range (IQR) (continuous variables). The association between fuel type (wood vs. charcoal) and respiratory health outcomes (cough, fever, short rapid breaths or ARI/severe ARI), was determined through multivariable logistic regression analysis; reporting the odds ratio (OR), 95% Confidence interval (95% CI) and level of significance (p-value). Univariable forward selection was used to determine variables for inclusion in the adjusted analysis. Covariates include, child’s age, sex, birth order, mode of delivery, vitamin A supplementation, breastfeeding, iron supplementation, maternal age, maternal education, wealth index, household smoking, cooking location, number of household remembers, season, place of residence, region. Statistical significance in the adjusted model was set at p < 0.05. Model collinearity was checked using variance inflation factors (VIF function in R). The primary analysis was performed upon the whole dataset, with subsequent sub-analyses by rural and urban area status respectively.

N/A

Based on the provided description, here are some potential innovations that can be used to improve access to maternal health:

1. Clean cooking technologies: Introducing and promoting the use of cleaner cooking technologies, such as electric stoves or biogas, can help reduce household air pollution associated with biomass burning. This can improve respiratory health outcomes for both mothers and children.

2. Education and awareness programs: Implementing education and awareness programs to inform communities about the health risks associated with wood and charcoal fuel usage can help promote behavior change. These programs can emphasize the importance of using cleaner fuels and provide information on the available alternatives.

3. Subsidies and incentives: Providing subsidies or incentives for households to switch to cleaner cooking fuels can make them more affordable and accessible. This can encourage more households to adopt cleaner technologies and reduce their reliance on wood and charcoal.

4. Infrastructure development: Investing in infrastructure development, such as expanding access to electricity or piped gas, can provide households with alternative energy sources for cooking. This can reduce the dependence on biomass fuels and improve respiratory health outcomes.

5. Policy interventions: Implementing and enforcing policies that regulate the use of biomass fuels and promote the adoption of cleaner cooking technologies can have a significant impact. These policies can include stricter emission standards, tax incentives for cleaner fuels, and regulations on the sale and use of wood and charcoal.

It is important to note that these recommendations are based on the information provided and may need to be tailored to the specific context and needs of the community in Uganda.
AI Innovations Description
The study investigated the association between wood and charcoal domestic cooking, respiratory symptoms, and acute respiratory infections (ARI) among children under 5 years old in Uganda. The findings showed that households using wood fuel had a higher risk of respiratory symptoms compared to those using charcoal fuel. Specifically, wood fuel use was associated with an increased risk of shortness of breath, fever, cough, ARI, and severe ARI. This association was observed in both urban and rural areas, although the risk was higher in urban areas for shortness of breath and ARI, and in rural areas for ARI and fever.

To improve access to maternal health, the following recommendations can be developed from this study:

1. Promote the use of cleaner cooking fuels: Encourage households to transition from wood and charcoal fuels to cleaner alternatives such as electricity, LPG, natural gas, or biogas. This can be achieved through awareness campaigns, subsidies, and incentives.

2. Improve cooking technologies: Develop and promote efficient and clean cooking technologies that reduce the emission of harmful pollutants. This can include improved stoves, ventilation systems, and alternative cooking methods.

3. Increase access to clean fuels: Ensure availability and affordability of cleaner cooking fuels in both urban and rural areas. This can be achieved through market interventions, distribution networks, and partnerships with private sector entities.

4. Enhance education and awareness: Conduct educational programs to raise awareness about the health risks associated with wood and charcoal cooking fuels. Empower women and families with knowledge about the benefits of using cleaner fuels for maternal and child health.

5. Strengthen policy and regulation: Implement and enforce policies and regulations that promote the use of cleaner cooking fuels and technologies. This can include setting standards for emissions, providing incentives for adoption, and monitoring compliance.

By implementing these recommendations, access to maternal health can be improved by reducing the exposure of pregnant women and young children to harmful pollutants from domestic cooking fuels. This can lead to a decrease in respiratory symptoms and acute respiratory infections, ultimately improving the overall health and well-being of mothers and children.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Promote the use of cleaner cooking fuels: Encourage households to switch from solid biomass fuels (such as wood and charcoal) to cleaner fuels like electricity, LPG, natural gas, or biogas. This can be done through awareness campaigns, subsidies, and incentives.

2. Improve access to clean cooking technologies: Provide access to clean cooking technologies, such as improved cookstoves or efficient biomass stoves, that reduce the emissions of harmful pollutants. This can be done through distribution programs or financial support.

3. Strengthen healthcare infrastructure: Invest in healthcare facilities, especially in rural areas, to ensure that pregnant women have access to quality maternal health services. This includes improving the availability of skilled healthcare providers, essential medicines, and equipment.

4. Enhance community-based interventions: Implement community-based interventions that focus on educating and empowering women and their families about maternal health. This can include training community health workers, conducting awareness campaigns, and providing support groups for pregnant women.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify key indicators that measure access to maternal health, such as the number of antenatal care visits, skilled birth attendance, postnatal care utilization, and maternal mortality rates.

2. Collect baseline data: Gather data on the current status of these indicators in the target population. This can be done through surveys, interviews, or existing data sources.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the selected indicators. This model should consider factors such as population size, geographical distribution, and socio-economic characteristics.

4. Input data and parameters: Input the baseline data and parameters into the simulation model. This includes information on the current usage of solid biomass fuels, healthcare infrastructure, and community-based interventions.

5. Simulate scenarios: Run the simulation model with different scenarios that reflect the implementation of the recommendations. This can involve changing variables such as the percentage of households using cleaner cooking fuels, the availability of clean cooking technologies, or the coverage of community-based interventions.

6. Analyze results: Analyze the simulation results to assess the impact of the recommendations on the selected indicators. This can include comparing the outcomes of different scenarios and identifying the most effective interventions.

7. Refine and validate the model: Refine the simulation model based on the analysis results and validate it using additional data or expert input. This ensures that the model accurately represents the real-world situation and can be used for future predictions.

By following this methodology, policymakers and stakeholders can gain insights into the potential impact of different recommendations on improving access to maternal health and make informed decisions on implementing the most effective interventions.


Statistics:
Citations: 12
Identifiers:
DOI: 10.3390/ijerph17113974
ISSN: 16617827
Research Areas:
Environmental, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants
Study Countries:
Uganda
Study Design:
Case-Control Study, Cross Sectional Study, Grounded Theory
Study Approach:
Quantitative
Participants Gender:
Male & Female
Partagez ceci :
Facebook
Twitter
LinkedIn
WhatsApp
Email